Identification of soil erosion and fluvial sediment problems

A computer model has been used to estimate soil loss and sediment yield from irregular field-size units of small watersheds. Input to the model includes spring data (i.e. relating to February through May) for the independent variables of the Universal Soil Loss Equation, and for factors such as surface roughness, an index of overland runoff, and proximity to the stream. Output from the model includes maps of seasonal estimates of potential soil losses, field sediment delivery ratios, and expected sediment yields. On the basis of selected erosion and sediment yield tolerances, the output information has been analysed to identify watershed areas which (1) exhibit both erosion and sediment yield problems; (2) exhibit only erosion problems; (3) exhibit only sediment yield problems; and (4) exhibit neither erosion nor sediment yield problems. The percentage of the watershed area in each category and the percentage of the watershed soil loss and sediment loads contributed by each category are also identified. Application of the procedure for planning remedial control programs for five watersheds is discussed.     

Soil erosion and conservation on land cultivated and drained for afforestation

Erosion of soil from pre-afforestation plough furrows has been measured on four soil types in Scotland for 12 to 18 month periods between 1987 and 1990. Rainfall-run-off was also measured at one site. Run-off is directly proportional to furrow length and rainfall intensity, and for a wide range of intensities (typically > 6 mm hr^?1) small amount of soil is flushed out of the furrows. However, for furrow spacings of 3.8 m, a critical downslope run-off increment associated with significant soil loss is of the order of 25 cm³ s^?1 m^?1, which is in accord with a storm of five years return period and a maximum intensity of 25 mm hr^?1. The total run-off volume for any hydrograph is commensurate with the total rainfall in the rainstorm — typically 40–80% by the hydrograph peak and approaching 100% by the end of the hydrograph; i.e. long term storage is negligible. A positive relationship was recorded between furrow length, slope angle and sediment yield, with deposition predominating in furrows less than 30 m in length on slopes less than a few degrees. Soil loss is proportional to the excess streampower expended by the run-off with an exponent in the range 1–1.5. For the soils examined, significant differences in soil loss when comparing sites for low power expenditure become undifferentiated at high power expenditures. For the rainfall regimes monitored, maximum soil losses were in the region of 40 kg per meter run-length of furrow, when soil peds were ripped from the bed. Laboratory data concerning the critical erosion threshold power and shear stress to erode soil peds are in general accord with the threshold furrow run-lengths defined using the field data for a five year storm and the soil losses observed.     

Mapping of erosion rates in marly badlands based on a coupling of anatomical changes in exposed roots with slope maps derived from LiDAR data

Black marls form very extensive outcrops in the Alps and constitute some of the most eroded terrains, thus causing major problems of sedimentation in artificial storage systems (e.g. reservoirs) and river systems. In the experimental catchments near Draix (France), soil erosion rates have been measured in the past at the plot scale through a detailed monitoring of surface elevation changes and at the catchment scale through continuous monitoring of sediment yield in traps at basin outlets. More recently, erosion rates have been determined by means of dendrogeomorphic techniques in three monitored catchments of the Draix basin. A total of 48 exposed roots of Scots pine have been sampled and anatomical variations in annual growth rings resulting from denudation analysed. At the plot scale, average medium‐term soil erosion rates derived from exposed roots vary between 1·8 and 13·8 mm yr^?1 (average: 5·9 mm yr^?1) and values are significantly correlated with slope angle. The dendrogeomorphic record of point‐scale soil erosion rates matches very well with soil erosion rates measured in the Draix basins. Based on the point‐scale measurements and dendrogeomorphic results obtained at the point scale, a linear regression model involving slope angle was derived and coupled to high‐resolution slope maps obtained from a LiDAR‐generated digital elevation model so as to generate high‐resolution soil erosion maps. The resulting regression model is statistically significant and average soil erosion rates obtained from the areal erosion map (5·8, 5·2 and 6·2 mm yr^?1 for the Roubine, Moulin and Laval catchments, respectively) prove to be well in concert with average annual erosion rates measured in traps at the outlet of these catchments since 1985 (6·3, 4·1 and 6·4 mm yr^?1). This contribution demonstrates that dendrogeomorphic analyses of roots clearly have significant potential and that they are a powerful tool for the quantification and mapping of soil erosion rates in areas where measurements of past erosion is lacking. Copyright © 2011 John Wiley & Sons, Ltd.     

An evaluation of the universal soil loss equation and field techniques for assessing soil erosion on a tropical alfisol in western Nigeria

Four techniques for soil erosion assessment were compared over two consecutive seasons for bare-fallow plots and a maize-cowpea sequence in 1985 at IITA, Ibadan, Nigeria. The techniques used were: tracer (aluminium paint), nails (16 and 25), the rill method, and the Universal Soil Loss Equation (USLE). Soil loss estimated by these techniques was compared with that determined using the runoff plot technique. There was significantly more soil loss (P < 0·01) in bare-fallow than in plots under maize (Zea mays) or cowpea (Vigna unguiculata). In the first season, soil loss from plots sown to maize was 40·2 Mg ha^?1 compared with 153·3 Mg ha^?1 from bare-fallow plots. In the second season, bare-fallow plots lost 87·5 Mg ha^?1 against 39·4 Mg ha^?1 lost from plots growing cowpea. The techniques used for assessing erosion had no influence on the magnitude of soil erosion and did not interfere with the processes of erosion. There was no significant difference (P < 0·05) between soil erosion determined by the nails and the runoff plot technique. Soil loss determined on six plots (three under maize, three bare-fallow) by the rill technique, at the end of the season, was significantly lower (P < 0·05) than that determined by the runoff plot technique. The soil loss estimated by the rill method was 143·2, 108·8 and 121·9 Mg ha^?1 for 11, 11, and 8 per cent slopes respectively, in comparison with 201·5, 162·0, and 166·4 Mg ha^?1 measured by the runoff plot method. Soil loss measured on three bare-fallow plots on 10 different dates by the rill technique was also significantly lower (P < 0·01) than that measured by the runoff plot. In the first season the USLE significantly underestimated soil loss. On 11, 11, and 8 per cent slopes, respectively, soil loss determined by the USLE was 77, 92, and 63 per cent of that measured by the runoff plot. However, in the second season there was no significant difference between soil loss determined by the USLE and that determined by the conventional runoff plot technique.     

Impact of land use changes on catchment soil erosion and sediment yield in the northeastern China: A panel data model application

Land use is an important factor influencing soil erosion and sediment yield (SESY). Regressing soil erosion intensity (SEI) and sediment yield (SY) to land use characteristics can provide necessary information for controlling soil loss. However, current simple regression methods emphasize cross sectional parameters, with less emphasis on temporal variability of relevant land use parameters so that the derived effects of land use change on SESY can be biased. Here, a panel data method was applied to quantify the impact of land use change on SESY in 1954, 1975, and 2015, based on the WaTEM/SEDEM model and seven landscape metrics for 25 reservoir catchments in northeastern China. The results indicate that SEI and area-specific SY (SSY) continuously decreased from 1954 to 2015, which were significantly correlated with landscape metrics such as area-edge metrics of mean patch area (AREA_MN), shape index of the mean related circumscribing circle (CIRCLE_MN), aggregation index of effective mesh size (MESH), patch cohesion index (COHESION), and diversity metrics such as Shannon's diversity index (SHDI), patch richness density (PRD), and modified Simpson's evenness index (MSIEI). The results suggested that catchment SESY can be reduced through decreasing mean patch area, patch mesh size, and physical connectivity of patches, enriching landscape types, and elongating land use patches. These findings are helpful to effectively implement soil conservation measures in northeastern China and similar regions worldwide. The current study also implies that the panel data approach will have beneficial potential applications in earth-science research fields.