Modeling potential erosion due to the Cerro Grande Fire with a GIS-based implementation of the Revised Universal Soil Loss Equation

Erosional processes directly influenced by wildland fire include reduction or elimination of above- ground biomass, reduction of soil organic matter, and hydrophobicity. High fuel loads promoted by decades of fire suppression in the U.S. increase the duration and intensity of burning, amplifying these effects. The Cerro Grande fire (6–31 May 2000) consumed approximately 15 000 hectares around and within the town of Los Alamos, New Mexico, USA. Private and public infrastructure including Los Alamos National Laboratory are at continuing risk due to increased threats of upstream erosion. We use a geographic information system (GIS) based implementation of the Revised Universal Soil Loss Equation (RUSLE) to model pre- and post-fire soil loss conditions and aid erosion risk analysis. Pre- and post-fire vegetation cover data layers were generated from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data. Based upon annual average rainfall amounts we estimate that subwatershed average pre-fire erosion rates range from 0.45 to 9.22 tonnes ha–1 yr–1 while post-fire erosion rates before watershed treatments range from 1.72 to 113.26 tonnes ha–1 yr–1. Rates are approximately 3.7 times larger for 50 year return interval rainfall amounts. It is estimated that watershed treatments including reseeding will decrease soil loss between 0.34 and 25.98% in the first year on treated subwatersheds. Immediately after the fire an interagency Burned Area Emergency Rehabilitation (BAER) team produced initial estimates of soil erosion. Our estimates of average erosion rates by subwatershed were in general larger than those initial estimates.

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Estimation of Soil Loss Using Remote Sensing And GIS-Based Universal Soil Loss Equation In Northern Catchment of Lake Tana Sub-Basin, Upper Blue Nile Basin, Northwest Ethiopia

10.21203/rs.3.rs-78824/v1 ◽

2020 ◽

Author(s):

Veera Narayana Balabathina ◽

Raju RP ◽

Wuletaw Mulualem ◽

Gedefaw Tadele

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Lake Tana ◽

Erosion Risk ◽

Priority Areas ◽

Erosion Rates ◽

The Mean ◽

Soil Loss Equation

Abstract Background: Soil erosion, one of the major environmental challenges, is influenced by topography, climate, soil characteristics, and human activities and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. The present study attempts to estimate soil erosion risk in the Northern catchment of Lake Tana basin, situated in northwest part of Ethiopia, with available data through the application of the Universal Soil Loss Equation model integrated with Geographic Information System and remote sensing technologies to identify priority areas for controlling soil erosion. In addition, it analyzes the effect of land use and land cover, topography, erodibility, and drainage density on soil erosion potential of the catchment, and the possible relationships among them. Results: The results show that the mean annual soil loss of catchment is estimated at 37.89 ± 59.2 t ha−1yr−1 with a total annual soil loss of 1,705,370 tons. The topography (LS-factor), followed by the support practice (P-factor) and the soil erodibility (K-factor) were the most sensitive factors affecting soil erosion in the catchment. To identify high priority areas for management, the study area was subdivided into five major sub-basins and further categorized into five erosion classes based on erosion severity. The mean soil erosion rates of the Derma, Megech, Gumara, Garno, and Gabi Kura River sub-basins are 46.8, 40.98, 30.95, 30.04, and 29.66 t ha−1yr−1, respectively. About 58.9% of the area was found in very low erosion risk which extends from 0-1 t ha−1yr−1 and accounted only 1.1% of total soil loss, while 12.4% of the area was found to be under high and extreme erosion risk with erosion rates of 10 t ha−1yr−1 or more that contributes about 82.1% of total soil loss warrant high priority for reducing the risk of soil erosion. Conclusions: This study permits the understanding of the soil erosion process and the various factors that lead to the spatial variability of the risk in the catchment, and thus enhances the effectiveness of proposed conservation strategies for sustainable land management.

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