Remote Sensing in Hydrology and Water Management || Soil Erosion
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12 Soil Erosion
Jerry C. Ritchie USDA-ARS Hydrology Laboratory, BARe-West, Bldg-007, Beltsville, MD 20705 USA
12.1 Introduction Soil erosion is a natural procds caused by water, wind, and ice that has affected the earth's surface since the beginning of time. Soil erosion and its off-site, downstream damages are major concerns around the world (Lal 1994b) causing losses in soil productivity and degradation oflandscape (Walling 1983). Many of man's activities have accelerated soil erosion (Sombroek 1995; Walling 1983). Oldeman (1994) has estimated that human-induced soil degradation has affected 15% of the world's arable land surface. Estimates of global soil erosion rates range from 0.088 rom yr-l (Walling 1987) to 0.30 rom yr-l (Fournier 1960). These values led to estimates of 17.4 to 58.1 x 109 Mg of soil loss from the land surface (Walling 1990) which is carried down-stream into lakes, reservoirs and estuaries where it reduces storage capacity and affects water quality, navigation, and biological productivity. On the land surface, soil erosion decreases organic matter, fme grained soil particles, water holding capacity, and rooting depth leading to loss of soil productivity and quality. The economic consequences from soil erosion on loss of productivity, land degradation, and off-site, downstream damages from eroded soil particles on water quality are a major concern. Pimentel et al. (1995) estimated the economic cost of soil erosion and subsequent sediment deposition to be $400 billion per year worldwide. While this economic estimate of the cost of erosion has been questioned (Sombroek 1995), concerns about soil loss and the estimated cost point to the need for new and improved methodologies and techniques for monitoring and quantifYing soil erosion effectively and efficiently across the landscape so that effective land management practices can be applied to the land surface to control and reduce soil erosion.
Determining spatially distributed soil erosion on the landscape using classical soil erosion measurement techniques is difficult, time consuming, and expensive (Braken-siek et al. 1979; LalI994a). These techniques involve field studies with experimental plots to establish basic principles and measure rates of erosion. Small unit-source catchments are used for relating these plot studies to larger areas (Mutchler et al. 1994). These types of studies involve continuous measurements of soil and water movement from plots/catchments and require long time periods (years) of data collection to provide statistically significant results. Such studies are limited to establishing information about processes and rates and can seldom be used to
G. A. Schultz et al. (eds.), Remote Sensing in Hydrology and Water Management Springer-Verlag Berlin Heidelberg 2000
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determine spatial patterns of soil erosion. Others techniques involve measuring sediment loads at the outlet of catchments and relating these measured sediment loads to soil erosion on the catchment using sediment delivery ratios (Walling 1983). However, estimating soil erosion rates from sediment loads by sediment delivery ratios has long been recognized as a problem (Roehl 1962; Walling 1983) and provides no information on spatial patterns. Radioactive fallout (I37Cesium) and naturally occurring radioactive elements (i.e., 21Opb) have also been used to measure soil erosion and sediment deposition (Ritchie and McHenry 1990). The use of radionuclides allows the measurement of both eroding and depositing sites within a field and thus provides better information on actual soil loss from a field and the spatial patterns of erosion and deposition within a field. Detailed information on classical field techniques for measuring soil erosion can be found in a field manual of methods for agricultural hydrology (Brakensiek et al. 1979) and a recent review of soil erosion measurement techniques is presented by La} (l994a).
In addition to field measurements of soil erosion, empirical and process-based mathematical equations/models have been developed to estimate soil erosion (Foster 1991; Lane et al. 1992). The most widely used soil erosion model is the Universal Soil Loss Equation (USLE) which is an empirically based equation developed from data collected from standard soil erosion plots on "typical" soils of the United States east of the Rocky Mountains (Wischmeier and Smith 1978). The USLE has been extensively used and ,,misused" in the United States and around the World. Even with its limitations, the USLE is the most widely used, powerful and practical management tool for estimating sheet and rill erosion on agricultural landscapes. A Revised Universal Soil Loss Equation (RUSLE) using the same form and factors with revised coefficients is available with applications to a wider range of conditions and locations than the original USLE but is still based on empirical relationships (Renard et al. 1991, 1997). The form of the equation for the RUSLE (and USLE) is:
Where A is the average annual soil loss per unit area; R, the rainfall factor; K, the soil erodability factor; L, the slope length factor; S, the slope steepness factor; C, the crop management factor; and P, the soil erosion control practice factor. Numerical coefficients for these factors were determined empirically from field and laboratory data (Wischmeier and Smith 1978; Renard et al. 1997). Many other efforts to develop empirical and physically-based models of soil erosion and its off-site effects have been made that have had varying degrees of success and applications in management and research. A general discussion of soil erosion models with a more in depth view of their applications and limitations is given by Foster (1991), Lane et al. (1992) and Lal (1994a).
The limitations of current measurement techniques and models to provide informa-tion on the spatial and temporal distribution of soil erosion across catchments and on the movement of eroded particles into streams limit our ability to develop cost-effective land management strategies for erosion control. Such limitations point to the need to investigate other techniques to supplement current techniques for monitoring
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and quantifying soil erosion rates and patterns and the need for techniques that can identify potential as well as actual source areas of soil erosion on the landscape.
Soil erosion causes both physical (i.e., gullies, rills) and visible (i.e., exposure of different colored soil layers) changes in the surface properties of soils on the land-scape. Such changes can be measured both spatially and temporally using remote sensing techniques with a variety of sensors and sensor platforms. Remote sensing techniques can measure qualitative and quantitative information on changes in the soil surface roughness and on visible features. Remote sensing techniques to measure eroded material once it leaves the land surface and enters a stream or a water body are discussed in Chap. 13 of this book.
12.2 Basis for using Remote Sensing Cihlar (1987) concluded that assessing and monitoring soil erosion occurs in two dimensions that he called stage and time. He uses stage to refer to the type of soil erosion (i.e., sheet, rill, or gully) and time to refer to actual or potential soil erosion. It is important to evaluate both the stage and time dimension if we are to develop management plans to reduce or control soil erosion. Both the stage and time of erosion can affect the physical and spectral properties of soil surfaces. Since remote sensing techniques measure spectral and physical properties, we can use remote sensing to provide information on these changes in surface properties of the soil caused by erosion. Remote sensing techniques can provide spatial and temporal data on these properties that will allow us to develop better management plans for large areas to reduce soil erosion.
Remote sensing techniques that measure the spectral properties of the landscape are most commonly applied to study soil erosion patterns and rates. Ground-based and aerial photographs are still the most popular remote sensing technique used to study and map soil erosion using either photo interpretation or photogrammetric techniques. These techniques provide information on spectral differences in the soil surface and are interpreted to delineate areas affected by soil erosion. Photointerpretation of images made from digital radiance data from satellite sensors (Landsat, SPOT, IRS, A VHRR, etc.) is also widely used to map areas of soil degradation. Photographs and digital imagery have been used for mapping actual/potential soil erosion areas, for determining spectral patterns and differences in the surface soils related to soil erosion, and for determining land cover and conservation practices for input to soil erosion models.
Photogrammetric techniques are used with stereo photographs to measure physical changes (i.e., roughness) in soil surface elevation. Sequential photographs can be used to determine changes in areas of erosion or deposition over time. Ground-based and airborne lasers are also used to measure landscape surface roughness and topography. These laser systems can measure physical changes in the soil surface to within a few millimeters from ground platforms and within a few centimeters,from aerial platforms allowing estimates of soil loss or estimates of surface roughness that allow us to better understand soil erosion. Synthetic aperture radar (SAR) also has been used to measure
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the landscape topography and may have potential applications for evaluating large-scale soil erosion patterns and rates.
While remote sensing data can be used alone to access soil erosion rates and pat-terns, a combination of remote sensing data, soil