Modeling Rainfall Erosivity From Daily Rainfall Events, Upper Blue Nile Basin, Ethiopia

Nigussie, Tewodros Assefa; Fanta, Abebe; Melesse, Assefa M.; Quraishi, Shoeb

doi:10.1007/978-3-319-02720-3_17

Cited by 5 publications

(7 citation statements)

References 13 publications

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“…Calculated rainfall erosivity (R) factor values for rangeland and cropland sites are presented in Table S1. These R‐factor values ranging from 1,638 to 3,903 (Table S1) for the different sites are in line with reported R‐factor values for semi‐arid environments with measured rainfall intensity (Figure S1; Haile et al, ; Angima et al, ; Stillhardt et al, ; Nigussie et al, ). The variability of R‐factor values between years and sites is related to variation in rainfall depth (Table S1).…”

Section: Resultssupporting

confidence: 88%

“…The variability of R‐factor values between years and sites is related to variation in rainfall depth (Table S1). Nigussie et al () also indicated that rainfall erosivity is the highest during July and August accounting for 81.6% of the annual erosivity in Ethiopia. The rainfall outside the rainy season is unreliable and less erosive (Nyssen et al, ), whereas rainfall during the main rainy season is erosive due to large drop sizes and the erratic nature of rainfall.…”

Section: Resultsmentioning

confidence: 97%

“…However, such data are very scarce for arid and semi‐arid climates where rainfall is highly variable. Empirical relationships between (daily, monthly, seasonal, or annual) rainfall depth and measured R‐factor values are therefore often used as an alternative approach (e.g., Hurni, ; Mati et al, ; Nigussie et al, ; Vrieling, Sterk, & de Jong, ). In this study, R was estimated as a function of seasonal rainfall depth (Ps) measured at each plot site, using an empirical equation for the Ethiopian Highlands (Hurni, ):

normalR = 5.5 * Ps - 47,

…”

Section: Methodsmentioning

confidence: 99%

“…As a consequence, researchers are often forced to guess values for these factors without knowing to what extent these values are representative for the implemented measures or the environment. This forms a major bottleneck for soil erosion prediction and understanding impacts of natural resource management in Ethiopia and many other developing countries (Karamage et al, ; Mati et al, ; Nigussie et al, ; Nyssen et al, ; Sonneveld, Keyzer, & Albersen, ). A further challenge is that, although several studies show that commonly applied SWC measures such as stone bunds and trenches are highly effective (Desta et al, ; Nyssen et al, , ; Taye et al, ), their effectiveness can also strongly decline over time, due to a decline in static storage capacity (SSC; Guzman et al, ; Taye et al, ).…”

Section: Introductionmentioning

confidence: 99%

“… Figure S1: Comparison of rainfall erosivity (R) factor values determined for the study area using seasonal rainfall (Ps) and Eq. 5 with published rainfall erosivity factor values from different stations in Ethiopia (ET), Eritrea (ER) and Kenya (KY) based on rainfall intensity measurements and their corresponding annual (Pa) or seasonal (Ps) rainfall depths (Angima, Stott, O'Neill, Ong, & Weesies, ; Haile, Herweg, & Stillhardt, ; Nigussie, Fanta, Melesse, & Quraishi, ; Stillhardt, Herweg, & Hurni, ). The regression line is for published data only.…”

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confidence: 99%

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Determining RUSLE P‐ and C‐factors for stone bunds and trenches in rangeland and cropland, North Ethiopia

et al. 2017

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The implementation of soil and water conservation (SWC) measures in the Ethiopian Highlands is a top priority to reduce soil erosion rates. However, the effectiveness of these measures for different hillslope gradients and land use conditions remains poorly understood. This study addresses this knowledge gap by determining support practice (P) and cover‐management (C) factors of the Revised Universal Soil Loss Equation for commonly used SWC structures in semi‐arid environments. The factor values were calculated on the basis of soil loss data collected with 21 large runoff plots installed in rangeland and cropland sites. The P‐ and C‐factors were calculated following the recommended procedures. Results show P‐factors ranging from 0.32 to 0.74 for stone bunds, from 0.07 to 0.65 for trenches, and from 0.03 to 0.22 for stone bunds with trenches. Reduced storage capacities due to sediment deposition resulted in significant declines of the effectiveness of SWC structures over time. For example, the average P‐factor value for trenches increased from 0.1 in the first year after installation to 0.51 after 3 years. C‐factor values ranged from 0.23 to 0.82 in rangeland and from 0.03 to 0.35 in cropland. For rangeland, this large variability is due to vegetation cover changes caused by grazing. In cropland, C‐factors vary with crop types and tillage practices. The results of this study not only aid in modelling and quantifying the short‐term impacts of SWC structures on soil erosion rates but also highlight the importance of considering temporal variations of the effectiveness of SWC measures.

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Section: Resultssupporting

confidence: 88%

Section: Resultsmentioning

confidence: 97%

normalR = 5.5 * Ps - 47,

…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Determining RUSLE P‐ and C‐factors for stone bunds and trenches in rangeland and cropland, North Ethiopia

et al. 2017

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Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province, southern China

Zhao

Liu

et al. 2015

Theor Appl Climatol

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Impacts of land use/land cover and climate changes on soil erosion in Muga watershed, Upper Blue Nile basin (Abay), Ethiopia

Belay

Mengistu

2021

Ecol Process

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Background Soil erosion is one of the major threats in the Ethiopian highlands. In this study, soil erosion in the Muga watershed of the Upper Blue Nile Basin (Abay) under historical and future climate and land use/land cover (LULC) change was assessed. Future LULC was predicted based on LULC map of 1985, 2002, and 2017. LULC maps of the historical periods were delineated from Landsat images, and future LULC was predicted using the CA–Markov chain model. Precipitation for the future period was projected from six regional circulation models. The RUSLE model was used to estimate the current and future soil erosion rate in Muga watershed. Results The average annual rate of soil erosion in the study area was increased from about 15 t ha−1 year−1 in 1985 to 19 t ha−1 year−1 in 2002, and 19.7 t ha−1 year−1 in 2017. Expansion of crop cultivation and loss of vegetation caused an increase in soil erosion. Unless proper measure is taken against the LULC changes, the rate of soil loss is expected to increase and reach about 20.7 t ha−1 year−1 in 2033. In the 2050s, soil loss is projected to increase by 9.6% and 11.3% under RCP4.5 and RCP8.5, respectively, compared with the baseline period. Thus, the soil loss rate is expected to increase under both scenarios due to the higher erosive power of the future intense rainfall. When both LULC and climate changes act together, the mean annual soil loss rate shows a rise of 13.2% and 15.7% in the future under RCP4.5 and RCP8.5, respectively, which is due to synergistic effects. Conclusions The results of this study can be useful for formulating proper land use planning and investments to mitigate the adverse effect of LULC on soil loss. Furthermore, climate change will exacerbate the existing soil erosion problem and would need for vigorous proper conservation policies and investments to mitigate the negative impacts of climate change on soil loss.

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Modeling Rainfall Erosivity From Daily Rainfall Events, Upper Blue Nile Basin, Ethiopia

Cited by 5 publications

References 13 publications

Determining RUSLE P‐ and C‐factors for stone bunds and trenches in rangeland and cropland, North Ethiopia

Determining RUSLE P‐ and C‐factors for stone bunds and trenches in rangeland and cropland, North Ethiopia

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province, southern China

Impacts of land use/land cover and climate changes on soil erosion in Muga watershed, Upper Blue Nile basin (Abay), Ethiopia

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