Nu- Fang

Broad area mapping of monthly soil erosion risk using fuzzy decision tree approach: integration of multi-source data within GIS

Soil erosion poses a serious problem for sustainable agriculture and the environment. There is a need to develop a simple and practical approach for broad area mapping of soil erosion risk that uses the uncertain but available information as input data within the constraints of reasonable cost and time. In this work, a predictive approach for conducting analytical erosion risk assessment across broad areas is developed, which combines a fuzzy decision tree (FDT), remote sensing and Geographic Information System (GIS). This approach is applicable to situations with a limited amount of input data and can easily adjust assessment factors according to actual need. In this study, four dominating factors affecting soil erosion were considered: soil, topography, land cover and climate. GIS thematic layers of these factors were constructed followed by fuzzified analysis through trapezoidal shaped membership functions. Based on subdivided erosion response units (ERUs), an optimal FDT was determined to classify monthly soil erosion risk into five levels. High-risk and very high-risk soil erosion in the study area is mainly concentrated from June to August, with July and August showing the highest risk covering more than 80% of the study area. November to March is dominated by low risk over more than 90% of the study area, while medium risk is dominant in April, May, September and October. Compared with field survey data, the fuzzy decision erosion risk assessment approach was shown to be applicable and economical for rapidly identifying and locating soil erosion risk with limited input data by means of remote sensing and GIS.

Evaluation of rainfall erosivity and its temporal variation in the Yanhe River catchment of the Chinese Loess Plateau

Abstract The potential of rain to generate soil erosion is known as the rainfall erosivity (R), and its estimation is fundamental for a better understanding of the erosive ability of certain rainfall events. In this paper, we investigated the temporal variations of rainfall erosivity using common daily rainfall data from four meteorological stations during 1956xa0to 1989 and 2008xa0toxa02010 periods in the Yanhe River catchment of the Chinese Loess Plateau. The adaptability of several simplified calculation models for R was evaluated and compared with the results of previous studies. An exponential model based on the modified Fournier index (MFI) was considered as the optimum for our study area. By considering the monthly distribution and coefficient of variation of annual precipitation, equations based on two indices, the MFI and its modification FF, produced a higher calculation accuracy than mean annual precipitation. The rainfall erosivity in the Yanhe River catchment has a remarkable interannual difference, with a seasonality index ranging from 0.69 to 1.05 and a precipitation concentration index from 14.51 to 27.46. In addition to the annual rainfall amounts, the extreme wave of monthly rainfall distribution also has an effect on the magnitude and temporal variation of rainfall erosivity, especially interannual variation. For long time series of rainfall erosivity, a trend coefficient r of −0.07 indicated a slight decline in erosivity in the Yanhe River catchment from 1956 to 2010.