Soil erosion–runoff relations on cultivated land: Insights from laboratory studies

Mamedov, A. I.; Levy, Guy J.

doi:10.1111/ejss.12759

Cited by 20 publications

(23 citation statements)

References 42 publications

(107 reference statements)

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“…Soil erosion is one of the most important environmental issues in the world (Yin and Li 2001). Soil erosion hazards involve damaging the aquatic and terrestrial environment by reducing nutrients, increasing runoff and affecting aquatic life (Langdale and Shrader 1982;Pimentel and Burgess 2013;Quinteiro et al 2017;Mamedov and Levy 2019). Soil erosion is divided into two major groups of water and wind erosions.…”

Section: Resultsmentioning

confidence: 99%

Assessment of check dams’ role in flood hazard mapping in a semi-arid environment

Sepehri

Ildoromi

Malekinezhad

et al. 2019

Geomatics, Natural Hazards and Risk

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This study aimed to examine flood hazard zoning and assess the role of check dams as effective hydraulic structures in reducing flood hazards. To this end, factors associated with topographic, hydrologic and human characteristics were used to develop indices for flood mapping and assessment. These indices and their components were weighed for flood hazard zoning using two methods: (i) a multi-criterion decision-making model in fuzzy logic and (ii) entropy weight. After preparing the flood hazard map by using the above indices and methods, the characteristics of the change-point were used to assess the role of the check dams in reducing flood risk. The method was used in the Ilanlu catchment, located in the northwest of Hamadan province, Iran, where it is prone to frequent flood events. The results showed that the area of 'very low', 'low' and 'moderate' flood hazard zones increased from about 2.2% to 7.3%, 8.6% to 19.6% and 22.7% to 31.2% after the construction of check dams, respectively. Moreover, the area of 'high' and 'very high' flood hazard zones decreased from 39.8% to 29.6%, and 26.7% to 12.2%, respectively.

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Section: Resultsmentioning

confidence: 99%

Assessment of check dams’ role in flood hazard mapping in a semi-arid environment

Sepehri

Ildoromi

Malekinezhad

et al. 2019

Geomatics, Natural Hazards and Risk

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“…According to Mamedov and Levy (), the shape of the relationship between the measured soil loss, A e,m (M L −2 ), and the run‐off volume, Q e (L 3 L −2 ), depends on the processes and mechanisms that affect soil erosion. In particular, the authors distinguish between two categories: (a) conditions that contribute positively to surface aggregates and structural stability are characterized by a linear relationship and (b) conditions that promote formation of small aggregates and primary particles are characterized by a power‐type relationship.…”

Section: Discussionmentioning

confidence: 99%

“…In nearly all cases, that is, with a single exception, the highest R 2 values were detected for the power relationship. Therefore, the applicability of the USLE-MM and the USLE-MB can be physically justified with the occurrence of the second category by Mamedov and Levy (2019). In particular, these two models seem to be preferentially usable in physical conditions in which small aggregates and primary particles develop due to soil destabilization processes.…”

Section: Discussionmentioning

confidence: 99%

“…For both models, a distinction can be made between the event rainfall-run-off erosivity factor (EI 30 Q 1:2 R and EI b2 30 Q 1:2 R , respectively) and the event soil erodibility factor (K MB,e = Q b1 − 1:2 R K MB and (Bagarello et al, 2012;Mutchler & Carter, 1983;Torri et al, 2006). According to Mamedov and Levy (2019), the shape of the relationship between the measured soil loss, A e,m (M L −2 ), and the run-off volume, Q e (L 3 L −2 ), depends on the processes and mechanisms that affect soil erosion. In particular, the authors distinguish between two categories: (a) conditions that contribute positively to surface aggregates and structural stability are characterized by a linear relationship and (b) conditions that promote formation of small aggregates and primary particles are characterized by a power-type relationship.…”

Section: Discussionmentioning

confidence: 99%

“…Literature reports exponents of Q R EI 30 that vary rather widely, that is, from 0.87 (Shi, Huang, & Barbour, 2018) to 1.55 (Gao et al, 2012), and, according to Mamedov and Levy (2019) reasoning, differences in the exponents should be a consequence of different soil erosion processes and mechanisms. However, this investigation showed that they could also depend on the experimental information used to fit the model to the data .…”

Section: Discussionmentioning

confidence: 99%

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A comprehensive analysis of Universal Soil Loss Equation‐based models at the Sparacia experimental area

Bagarello

Ferro

Pampalone

2020

Hydrological Processes

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Improving Universal Soil Loss Equation (USLE)‐based models has large interest because simple and reliable analytical tools are necessary in the perspective of a sustainable land management. At first, in this paper, a general definition of the event rainfall‐ runoff erosivity factor for the USLE‐based models, REFe = (QR)b1(EI30)b2, in which QR is the event runoff coefficient, EI30 is the single‐storm erosion index, and b1 and b2 are coefficients, was introduced. The rainfall‐runoff erosivity factors of the USLE (b1 = 0 and b2 = 1), USLE‐M (b1 = b2 = 1), USLE‐MB (b1 ≠ 1 and b2 = 1), USLE‐MR (b1 = 1 and b2 ≠ 1), USLE‐MM (b1 = b2 ≠ 1), and USLE‐M2 (b1 ≠ b2 ≠ 1) can be defined using REFe. Then the different expressions of REFe were simultaneously tested against a data set of normalized bare plot soil losses, AeN, collected at the Sparacia (south Italy) site. As expected, the poorest AeN predictions were obtained with the USLE. The observed tendency of this model to overestimate small AeN values and underestimate high AeN values was reduced by introducing in the soil loss prediction model both QR and an exponent for the erosivity term. The fitting to the data was poor with the USLE‐MR as compared with the USLE‐MB and the USLE‐MM. Estimating two distinct exponents (USLE‐M2) instead of a single exponent (USLE‐MB, USLE‐MR, and USLE‐MM) did not appreciably improve soil loss prediction. The USLE‐MB and the USLE‐MM were recognized to be the best performing models among the possible alternatives, and they performed similarly with reference to both the complete data set and different sub‐data sets, only including small, intermediate, and severe erosion events. In conclusion, including the runoff coefficient in the soil loss prediction model is important to improve the quality of the predictions, but a great importance has to be paid to the mathematical structure of the model.

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Rates, factors, and tolerances of water erosion in the Cerrado biome (Brazil): A meta‐analysis of runoff plot data

Fonseca

Uagoda

Chaves

2021

Earth Surf Processes Landf

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Due to the high rainfall erosivity and highly erodible soils, water erosion is severe in Brazil. Soil and ecosystem degradation occurs when erosion exceeds on‐ and off‐site soil loss tolerances, with significant socioeconomic and environmental impacts. In the last 50 years, the Brazilian Cerrado had 53% of its original vegetation converted to agriculture and pastureland. Although erosion plot studies exist in the region, the data are fragmented and unexplored, hindering the development of soil conservation policies. The objective of the present research was to compile, systematize, and statistically analyze the existing erosion plot data in the Brazilian Cerrado, correlating the observed results with different environmental and management factors, and with the corresponding soil loss tolerances. Twenty runoff plot datasets of the Brazilian Cerrado, encompassing 5 states, 10 sites, 108 plots, and 360 plot·years were compiled and thoroughly analyzed. Mean annual rainfall, runoff, and soil loss were 1443.5 mm year−1, 83.1 mm year−1, and 8.9 Mg ha−1 year−1, respectively. After the data were normalized with respect to plot length, steepness, and climate, runoff and soil loss were found to be significantly higher in soils with impermeable horizons and in land uses without permanent soil cover (p < 0.05). Erosion under permanently covered plots was below the on‐ and off‐site soil loss tolerances. A power equation provided the best fit between plot runoff and soil loss (R2 = 0.71; p < 0.05), indicating that runoff volume, easier to estimate, could be used as a proxy for upslope erosion. Although erosion plot data cannot be extrapolated to the whole landscape, the research results provide useful elements for the development of sound conservation policies in the Cerrado and in other similar savannas of the world.

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Soil erosion–runoff relations on cultivated land: Insights from laboratory studies

Cited by 20 publications

References 42 publications

Assessment of check dams’ role in flood hazard mapping in a semi-arid environment

Assessment of check dams’ role in flood hazard mapping in a semi-arid environment

A comprehensive analysis of Universal Soil Loss Equation‐based models at the Sparacia experimental area

Rates, factors, and tolerances of water erosion in the Cerrado biome (Brazil): A meta‐analysis of runoff plot data

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