Potential impacts of climate change on soil erosion vulnerability across the conterminous United States

Abstract

Rainfall runoff erosivity (R) is one key climate factor that controls water erosion. Quantifying the effects of climate change-induced erosivity change is important for identifying critical regions prone to soil erosion under a changing environment. In this study we first evaluate the changes of R from 1970 to 2090 across the United States under nine climate conditions predicted by three general circulation models for three emissions scenarios (A2, A1B, and B1) from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Then, we identify watersheds that are most vulnerable to future climate change in terms of soil erosion potential. We develop a novel approach to evaluate future trends of R magnitude and variance by incorporating both the rate of change with time as well as the level of agreement between climatic projections. Our results show that mean decadal R values would increase with time according to all nine climatic projections considered between 1970 and 2090. However, these trends vary widely spatially. In general, catchments in the northeastern and northwestern United States are characterized by strong increasing trends in R, while the trends in the midwestern and southwestern United States are either weak or inconsistent among the nine climatic projections considered. The northeastern and northwestern United States will likely experience a significant increase in annual variability of R (i.e., increase in extreme events). Conversely the variability of R is unlikely to change in large areas of the Midwest. At the watershed scale (8-digit Hydrologic Unit Code), the mean vulnerability to erosion scores vary between -0.12 and 0.35 with a mean of 0.04. The five hydrologic regions with the highest mean vulnerability to erosion are 5, 6, 2, 1, and 17, with values varying between 0.06 and 0.09. These regions occupy large areas of Ohio, Maryland, Indiana, Vermont, and Illinois, with mean erosion vulnerability score statewide above 0.08. Future watershed management aiming at reducing soil erosion should focus on areas with the highest soil erosion vulnerability identified by this study.

Projected changes in US rainfall erosivity

“…The pattern of erosivity change estimated in our study from CMIP5 changes in F is consistent with what was found by Segura et al (2014) using just three models (with three scenarios each) from the older CMIP3 archive. But the pattern changes when we estimate erosivity with a different method: when erosivity is estimated from daily rainfall values, the multi-model mean indicates a decrease in Texas and the southern Great Plains, while an increase in erosivity is simulated by a majority of models when the estimate is done using monthly precipitation.…”

“…Others have looked at changes in F , as estimated from monthly mean precipitation changes in a handful of GCMs (global circulation models) (Nearing et al, 2004;Segura et al, 2014), and used the published relationship between R and F to deduce the change in erosivity. Others (e.g., Zhang et al, 2012) have temporally downscaled the GCM monthly output (by linking monthly rainfall totals to the transition probability between dry and wet days and using a weather generator to create daily time series) and used the downscaled precipitation in an erosion model to directly provide estimates of runoff and soil loss.…”

Climate change and erosion activities in Benin-Owena River Basin, S. W. Nigeria

“…It has been referred to as the detachment and removal of the topsoil either partially or completely. Soil erosion is the physical process by which soil particles are detached and removed from the ground surface by water and wind (Segura et al, 2014). Soil erosion threatens soil fertility due to nutrient and organic matter loss while also decreasing water quality through increased turbidity (Brown and Froemke, 2012).…”

“…Soil erosion may be expected to change in response to changes in climate for a variety of reasons, the most direct of which is the change in erosive power of rainfall (Nearing, 2001;Pruski and Nearing, 2002a). According to Segura et al (2014), rainfall runfall erosivity (R) is one key climate factor that controls water erosion. They identified the watersheds that are vulnerable to future climate change in terms of soil erosion potential.…”

Agricultural watershed modeling: a review for hydrology and soil erosion processes

“…RUSLE3D model has been applied to develop soil erosion risk maps mainly in developing countries (Beskow et al, 2009;Mello, 2014;Oliveira et al, 2014;Segura et al, 2014;Tang et al, 2015;Zhou et al, 2008). With the advent of geospatial computer resources, its application has allowed generating an easier and more accurate soil erosion risk map, supporting the engineers to identify spatially areas more susceptible to erosion and then, to target soil conservation practices more adequate.…”