GIS and remote sensing-based assessment of soil erosion risk using RUSLE model in South-Kivu province, eastern, Democratic Republic of Congo

Abstract

Soil erosion risk assessment in South-Kivu longs for the colonial epoch, while the province faces the problem of extreme degradation of land in the form of soil erosion. Thus, the study attempts to assess the soil erosion at the province level using the Revised Universal Soil Loss Equation (RUSLE) in conjunction with the Geographical Information System (GIS), and remote sensing data. The estimated total soil erosion was 2.084 million tons; with an annual average of 138.2 t ha À1 yr À1 . Moreover, the soil loss greater than 100 t ha À1 yr À1 accounts for 45.2% of the total erosive land. The soil erosion worsening nearly the entire territories range between 87 t ha À1 yr À1 in Shabunda to 248 t ha À1 yr À1 in Uvira. Under high aggressiveness of rainfall with mean of 1857.19 mm/y, the highest rate found in Perennial crop, Trees, and Cropland in contrast to Shrub and closed Forest was mainly due to the mean slope of 22% found in the former Land cover categories compared to 17% of Shrubland and closed forest. The adoption of terracing could reduce by 76% the current rate of cropland i.e., from (162.12 t ha À1 yr À1 to 38 t ha À1 yr À1 ). Therefore it is strongly recommended.

Evaluation of soil erosion and sediment yield spatio-temporal pattern during 1990–2019

“…K-factor shows the level of susceptibility of a soil type to detachment and transport during intense rainfall. The values closed to 0 are the least susceptible, the range between 0.2 and 0.4 is moderate and values greater than 0.4 are most susceptible (Kulimushi et al 2021).…”

“…The RUSLE is a popular model applied in several studies to assess the rill and interrill soil erosion (Kulimushi et al 2021;Kumar and Singh 2021).…”

“…Rainfall erosivity is a multifaceted process in which the amount, intensity, energy, duration, pattern, size of raindrops of rainfall, and associated runoff exerts influence . In tropical regions, Rainfall erosivity is estimated using Equation (2) proposed by Lo et al (1987) and employed in (Nambajimana et al 2020;Kulimushi et al 2021).…”

“…A low C-factor value is likely to generate lower soil erosion while the rate of soil erosion increase by increasing in C-factor value ( € Ozşahin and Ero glu 2019; Kulimushi et al 2021).…”

“…The erosivity increase from the middle part to the eastern, while the lowland in the northwest recorded a low erosivity. Nevertheless, Kulimushi et al (2021) stated that soil loss in tropical regions is not perfectly correlated with the R-factor. The Sebeya watershed is not an exception to the above statement because the current status of soil erosion shows high variation from the middle part toward western, northern, and southern inversely to the high variation of the erosivity from the central portion toward the eastern part of the watershed.…”